Overview

Dataset statistics

Number of variables33
Number of observations24865
Missing cells306043
Missing cells (%)37.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 MiB
Average record size in memory264.0 B

Variable types

NUM17
CAT12
BOOL2
UNSUPPORTED2

Warnings

dom has a high cardinality: 23278 distinct values High cardinality
opscope has a high cardinality: 20812 distinct values High cardinality
opfrom has a high cardinality: 6620 distinct values High cardinality
opto has a high cardinality: 5746 distinct values High cardinality
oploc has a high cardinality: 5351 distinct values High cardinality
enttypeitem is highly correlated with enttype and 2 other fieldsHigh correlation
enttype is highly correlated with enttypeitem and 2 other fieldsHigh correlation
enttypeminu is highly correlated with enttype and 2 other fieldsHigh correlation
forregcap is highly correlated with parnum and 1 other fieldsHigh correlation
parnum is highly correlated with forregcapHigh correlation
congro is highly correlated with forregcapHigh correlation
enttypegb is highly correlated with enttype and 2 other fieldsHigh correlation
enttypeitem has 8214 (33.0%) missing values Missing
opto has 16040 (64.5%) missing values Missing
empnum has 5250 (21.1%) missing values Missing
compform has 14234 (57.2%) missing values Missing
parnum has 22526 (90.6%) missing values Missing
exenum has 23487 (94.5%) missing values Missing
opform has 15866 (63.8%) missing values Missing
ptbusscope has 24865 (100.0%) missing values Missing
venind has 16428 (66.1%) missing values Missing
enttypeminu has 17595 (70.8%) missing values Missing
midpreindcode has 24865 (100.0%) missing values Missing
protype has 24831 (99.9%) missing values Missing
reccap has 17781 (71.5%) missing values Missing
forreccap has 24638 (99.1%) missing values Missing
forregcap has 24615 (99.0%) missing values Missing
congro has 24616 (99.0%) missing values Missing
empnum is highly skewed (γ1 = 64.09544801) Skewed
exenum is highly skewed (γ1 = 37.12059194) Skewed
regcap is highly skewed (γ1 = 37.58223561) Skewed
dom is uniformly distributed Uniform
opto is uniformly distributed Uniform
id has unique values Unique
ptbusscope is an unsupported type, check if it needs cleaning or further analysis Unsupported
midpreindcode is an unsupported type, check if it needs cleaning or further analysis Unsupported
empnum has 1100 (4.4%) zeros Zeros
reccap has 3641 (14.6%) zeros Zeros

Reproduction

Analysis started2020-12-01 09:18:44.266611
Analysis finished2020-12-01 09:20:19.222340
Duration1 minute and 34.96 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

id
Categorical

UNIQUE

Distinct24865
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
82750f1b9d122350631f2f1a07ab9386fdc3bbe8405dee2a
 
1
82750f1b9d12235051914b2ff47de9503ecb724a0685976c
 
1
da8691b210adb3f6f930cba2d98cbd1fab4b3514f5dac26f
 
1
d8071a739aa75a3be52776eaab98e82d9d2dfc8fff11b906
 
1
516ab81418ed215d7ff88dff6078f5b662836a2fa66329f5
 
1
Other values (24860)
24860 
ValueCountFrequency (%) 
82750f1b9d122350631f2f1a07ab9386fdc3bbe8405dee2a1< 0.1%
 
82750f1b9d12235051914b2ff47de9503ecb724a0685976c1< 0.1%
 
da8691b210adb3f6f930cba2d98cbd1fab4b3514f5dac26f1< 0.1%
 
d8071a739aa75a3be52776eaab98e82d9d2dfc8fff11b9061< 0.1%
 
516ab81418ed215d7ff88dff6078f5b662836a2fa66329f51< 0.1%
 
beb4aaaa89e0a0ae66f0bec42a60df9481549f3d5eefa8111< 0.1%
 
516ab81418ed215d8167596332520a089f98990d0d6ff8501< 0.1%
 
e9f7b28ec10e04704615292762fabc03c0da5451faa52c171< 0.1%
 
beb4aaaa89e0a0ae4270c78593a2fc3ea64441dd372d31a91< 0.1%
 
f000950527a6feb6b03cf0c5c7020228573603098f4b891a1< 0.1%
 
Other values (24855)24855> 99.9%
 
2020-12-01T17:20:19.564304image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique24865 ?
Unique (%)100.0%
2020-12-01T17:20:19.851121image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length48
Median length48
Mean length48
Min length48

oplocdistrict
Real number (ℝ≥0)

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean340210.5369
Minimum340000
Maximum340294
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:20.224036image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum340000
5-th percentile340200
Q1340202
median340207
Q3340221
95-th percentile340225
Maximum340294
Range294
Interquartile range (IQR)19

Descriptive statistics

Standard deviation12.81857312
Coefficient of variation (CV)3.767835422e-05
Kurtosis18.44865257
Mean340210.5369
Median Absolute Deviation (MAD)5
Skewness1.377265426
Sum8459334999
Variance164.3158168
MonotocityNot monotonic
2020-12-01T17:20:20.615820image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
340202548122.0%
 
340207412016.6%
 
340200344213.8%
 
340203300712.1%
 
34022524449.8%
 
34022120928.4%
 
34022318037.3%
 
34022213385.4%
 
3402086302.5%
 
3402714261.7%
 
Other values (6)820.3%
 
ValueCountFrequency (%) 
3400004< 0.1%
 
340200344213.8%
 
340201390.2%
 
340202548122.0%
 
340203300712.1%
 
ValueCountFrequency (%) 
3402941< 0.1%
 
340272360.1%
 
3402714261.7%
 
34022524449.8%
 
3402241< 0.1%
 

industryphy
Categorical

Distinct20
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
O
10312 
M
7017 
R
2968 
L
1428 
J
1130 
Other values (15)
2010 
ValueCountFrequency (%) 
O1031241.5%
 
M701728.2%
 
R296811.9%
 
L14285.7%
 
J11304.5%
 
P6252.5%
 
N5672.3%
 
Q3821.5%
 
F1140.5%
 
K870.3%
 
Other values (10)2350.9%
 
2020-12-01T17:20:20.978456image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T17:20:21.295024image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

industryco
Real number (ℝ≥0)

Distinct345
Distinct (%)1.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean7885.261141
Minimum0
Maximum9700
Zeros2
Zeros (%)< 0.1%
Memory size194.3 KiB
2020-12-01T17:20:21.638051image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6790
Q17512
median8040
Q38199
95-th percentile8930
Maximum9700
Range9700
Interquartile range (IQR)687

Descriptive statistics

Standard deviation667.0475452
Coefficient of variation (CV)0.08459422375
Kurtosis17.69240112
Mean7885.261141
Median Absolute Deviation (MAD)450
Skewness-2.126484947
Sum196059133
Variance444952.4276
MonotocityNot monotonic
2020-12-01T17:20:22.147273image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
8090309312.4%
 
829018997.6%
 
804018137.3%
 
751914976.0%
 
759013075.3%
 
811110264.1%
 
74999213.7%
 
73208293.3%
 
67607813.1%
 
88907693.1%
 
Other values (335)1092944.0%
 
ValueCountFrequency (%) 
02< 0.1%
 
731< 0.1%
 
891< 0.1%
 
1112< 0.1%
 
1412< 0.1%
 
ValueCountFrequency (%) 
97001< 0.1%
 
96201< 0.1%
 
94121< 0.1%
 
92912< 0.1%
 
92251< 0.1%
 

dom
Categorical

HIGH CARDINALITY
UNIFORM

Distinct23278
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
746df9aaed85785750564fb51c89c9c469347cef8c39195aa799082630881cfb19caa98fbb1572e2fb017e3568e479c31dec4a40478455f8
 
22
31487d8f256f16bd6244b7251be2ebb227ca54d864983f5d533d505d4e0d1ec9a4d6553d4439c868f7f1b6346371b63aa4fe635720f130b0
 
20
ca213febe80e171c3b9617e39b49d64eb1d41d39955a4494d2ca4fb0d71b236d664e8b882330b8a6
 
18
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b19ffcd2880f506783004837606b751aad0045609b733c27c0a26dfcf4f5a5528e1f77b54e7fe0652705b1979601dfee1c8982361cb59f1d005782249a6d6eb156a4908ee17f78b7e3649728a29f38c545
 
17
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b1e0da20e2aa30dc70bc1eeb69e2ce688edfb053255a8ab815
 
15
Other values (23273)
24773 
ValueCountFrequency (%) 
746df9aaed85785750564fb51c89c9c469347cef8c39195aa799082630881cfb19caa98fbb1572e2fb017e3568e479c31dec4a40478455f8220.1%
 
31487d8f256f16bd6244b7251be2ebb227ca54d864983f5d533d505d4e0d1ec9a4d6553d4439c868f7f1b6346371b63aa4fe635720f130b0200.1%
 
ca213febe80e171c3b9617e39b49d64eb1d41d39955a4494d2ca4fb0d71b236d664e8b882330b8a6180.1%
 
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b19ffcd2880f506783004837606b751aad0045609b733c27c0a26dfcf4f5a5528e1f77b54e7fe0652705b1979601dfee1c8982361cb59f1d005782249a6d6eb156a4908ee17f78b7e3649728a29f38c545170.1%
 
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b1e0da20e2aa30dc70bc1eeb69e2ce688edfb053255a8ab815150.1%
 
31487d8f256f16bd6244b7251be2ebb210b4e8f49f9331b0ab5741bea91606d9f42620fe82d891701e0d4018709b564e1ef0ec2f03b120e8150.1%
 
ca213febe80e171cf62c2ed671ebb5cb3432a52e67b170cb328e09384a40eaaf32b791a101af85856570013914ba7137150.1%
 
ca213febe80e171c3b9617e39b49d64eb1d41d39955a4494ee140c20d835dca2f8c73c67247f94b5150.1%
 
746df9aaed85785750564fb51c89c9c469347cef8c39195aa799082630881cfba6a0026ec3b03ebe130.1%
 
746df9aaed85785750564fb51c89c9c469347cef8c39195aa799082630881cfb19caa98fbb1572e2fb017e3568e479c3661bad53f846d1b112< 0.1%
 
Other values (23268)2470399.3%
 
2020-12-01T17:20:22.554522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique22335 ?
Unique (%)89.8%
2020-12-01T17:20:22.884160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length432
Median length128
Mean length137.6656344
Min length48

opscope
Categorical

HIGH CARDINALITY

Distinct20812
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
室内装修服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)
 
189
理发服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)
 
113
足浴服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)
 
82
企业投资(涉及前置许可的除外)。(依法须经批准的项目,经相关部门批准后方可开展经营活动)
 
68
理发服务(依法须经批准的项目,经相关部门批准后方可开展经营活动)
 
65
Other values (20807)
24348 
ValueCountFrequency (%) 
室内装修服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)1890.8%
 
理发服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)1130.5%
 
足浴服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)820.3%
 
企业投资(涉及前置许可的除外)。(依法须经批准的项目,经相关部门批准后方可开展经营活动)680.3%
 
理发服务(依法须经批准的项目,经相关部门批准后方可开展经营活动)650.3%
 
美发服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)620.2%
 
美容服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)610.2%
 
美容服务(依法须经批准的项目,经相关部门批准后方可开展经营活动)560.2%
 
洗浴服务。(依法须经批准的项目,经相关部门批准后方可开展经营活动)510.2%
 
足浴服务(依法须经批准的项目,经相关部门批准后方可开展经营活动)470.2%
 
Other values (20802)2407196.8%
 
2020-12-01T17:20:23.411330image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique19633 ?
Unique (%)79.0%
2020-12-01T17:20:24.050797image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length973
Median length66
Mean length89.97084255
Min length3

enttype
Real number (ℝ≥0)

HIGH CORRELATION

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4229.008647
Minimum1100
Maximum9600
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:24.354055image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1100
5-th percentile1100
Q11100
median1100
Q39600
95-th percentile9600
Maximum9600
Range8500
Interquartile range (IQR)8500

Descriptive statistics

Standard deviation3892.282453
Coefficient of variation (CV)0.9203770383
Kurtosis-1.564518628
Mean4229.008647
Median Absolute Deviation (MAD)0
Skewness0.5707719966
Sum105154300
Variance15149862.7
MonotocityNot monotonic
2020-12-01T17:20:24.643044image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
11001408556.6%
 
9600819332.9%
 
450021808.8%
 
21001410.6%
 
1200810.3%
 
2200400.2%
 
3100370.1%
 
3200290.1%
 
9100230.1%
 
5100200.1%
 
Other values (7)360.1%
 
ValueCountFrequency (%) 
11001408556.6%
 
1200810.3%
 
21001410.6%
 
2200400.2%
 
3100370.1%
 
ValueCountFrequency (%) 
9600819332.9%
 
9100230.1%
 
68002< 0.1%
 
6100190.1%
 
58003< 0.1%
 

enttypeitem
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct31
Distinct (%)0.2%
Missing8214
Missing (%)33.0%
Infinite0
Infinite (%)0.0%
Mean1646.959942
Minimum1110
Maximum9600
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:24.932952image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1110
5-th percentile1130
Q11130
median1150
Q31150
95-th percentile4540
Maximum9600
Range8490
Interquartile range (IQR)20

Descriptive statistics

Standard deviation1276.284531
Coefficient of variation (CV)0.77493356
Kurtosis7.185926114
Mean1646.959942
Median Absolute Deviation (MAD)20
Skewness2.588714536
Sum27423530
Variance1628902.205
MonotocityNot monotonic
2020-12-01T17:20:25.226446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%) 
1130746730.0%
 
1150567922.8%
 
453014225.7%
 
11908433.4%
 
45407573.0%
 
1220790.3%
 
1110790.3%
 
2130770.3%
 
9600710.3%
 
2150360.1%
 
Other values (21)1410.6%
 
(Missing)821433.0%
 
ValueCountFrequency (%) 
1110790.3%
 
112010< 0.1%
 
1130746730.0%
 
11407< 0.1%
 
1150567922.8%
 
ValueCountFrequency (%) 
9600710.3%
 
68102< 0.1%
 
61801< 0.1%
 
61504< 0.1%
 
61201< 0.1%
 

opfrom
Categorical

HIGH CARDINALITY

Distinct6620
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
2019-12-11 00:00:00
 
38
2018-03-07
 
36
2019-11-27 00:00:00
 
34
2019-12-04 00:00:00
 
34
2019-12-16 00:00:00
 
34
Other values (6615)
24689 
ValueCountFrequency (%) 
2019-12-11 00:00:00380.2%
 
2018-03-07360.1%
 
2019-11-27 00:00:00340.1%
 
2019-12-04 00:00:00340.1%
 
2019-12-16 00:00:00340.1%
 
2019-11-07 00:00:00330.1%
 
2019-04-25330.1%
 
2019-11-21 00:00:00330.1%
 
2019-04-08330.1%
 
2019-12-05 00:00:00320.1%
 
Other values (6610)2452598.6%
 
2020-12-01T17:20:25.582995image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3348 ?
Unique (%)13.5%
2020-12-01T17:20:25.892832image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length19
Mean length14.7723708
Min length10

opto
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct5746
Distinct (%)65.1%
Missing16040
Missing (%)64.5%
Memory size194.3 KiB
2022-10-31
 
24
2029-08-15
 
16
2029-04-24
 
15
2046-12-06
 
14
2026-05-15
 
13
Other values (5741)
8743 
ValueCountFrequency (%) 
2022-10-31240.1%
 
2029-08-15160.1%
 
2029-04-24150.1%
 
2046-12-06140.1%
 
2026-05-15130.1%
 
2023-02-17130.1%
 
2047-12-25130.1%
 
2023-01-0511< 0.1%
 
2026-01-2610< 0.1%
 
2015-05-15 00:00:0010< 0.1%
 
Other values (5736)868634.9%
 
(Missing)1604064.5%
 
2020-12-01T17:20:26.252638image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4127 ?
Unique (%)46.8%
2020-12-01T17:20:26.542475image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length3
Mean length6.817856425
Min length3

state
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.164568671
Minimum4
Maximum20
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:26.852140image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6
Q16
median6
Q36
95-th percentile7
Maximum20
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5822263236
Coefficient of variation (CV)0.09444721192
Kurtosis79.96544229
Mean6.164568671
Median Absolute Deviation (MAD)0
Skewness7.510151697
Sum153282
Variance0.3389874919
MonotocityNot monotonic
2020-12-01T17:20:27.133137image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
62158386.8%
 
7310912.5%
 
111040.4%
 
13650.3%
 
43< 0.1%
 
201< 0.1%
 
ValueCountFrequency (%) 
43< 0.1%
 
62158386.8%
 
7310912.5%
 
111040.4%
 
13650.3%
 
ValueCountFrequency (%) 
201< 0.1%
 
13650.3%
 
111040.4%
 
7310912.5%
 
62158386.8%
 

orgid
Real number (ℝ≥0)

Distinct78
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.416681858e+17
Minimum1.4108e+17
Maximum4e+17
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:27.428725image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1.4108e+17
5-th percentile3.402e+17
Q13.402e+17
median3.4020201e+17
Q33.4020701e+17
95-th percentile3.4022301e+17
Maximum4e+17
Range2.5892e+17
Interquartile range (IQR)7.010009883e+12

Descriptive statistics

Standard deviation1.107348844e+16
Coefficient of variation (CV)0.03241006596
Kurtosis95.65478901
Mean3.416681858e+17
Median Absolute Deviation (MAD)2.010009888e+12
Skewness-0.3781296071
Sum-8.369577417e+18
Variance1.226221462e+32
MonotocityNot monotonic
2020-12-01T17:20:27.972227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3.4020201e+17361714.5%
 
3.4020701e+17289211.6%
 
3.402e+1722619.1%
 
3.4020301e+1720988.4%
 
3.4022101e+1713615.5%
 
3.4020017e+1711134.5%
 
3.402e+1710784.3%
 
3.4022301e+179293.7%
 
3.4022201e+176622.7%
 
3.402e+175492.2%
 
Other values (68)830533.4%
 
ValueCountFrequency (%) 
1.4108e+17180.1%
 
3.402e+1722619.1%
 
3.402e+17360.1%
 
3.402e+174311.7%
 
3.402e+17640.3%
 
ValueCountFrequency (%) 
4e+17200.1%
 
4e+17270.1%
 
4e+171660.7%
 
4e+1711< 0.1%
 
4e+172711.1%
 

jobid
Real number (ℝ≥0)

Distinct434
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.548101216e+17
Minimum1.4108e+17
Maximum4e+17
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:28.354280image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1.4108e+17
5-th percentile3.402e+17
Q13.402e+17
median3.402e+17
Q34e+17
95-th percentile4e+17
Maximum4e+17
Range2.5892e+17
Interquartile range (IQR)5.98e+16

Descriptive statistics

Standard deviation3.052366894e+16
Coefficient of variation (CV)0.0860281798
Kurtosis11.15271658
Mean3.548101216e+17
Median Absolute Deviation (MAD)19889792
Skewness-1.068803396
Sum4.810006954e+18
Variance9.316943655e+32
MonotocityNot monotonic
2020-12-01T17:20:28.700857image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3.402e+1717837.2%
 
3.402e+1717036.8%
 
3.402e+1711774.7%
 
3.402e+1710354.2%
 
4e+178313.3%
 
3.402e+175442.2%
 
3.402e+175352.2%
 
3.402e+174972.0%
 
4e+173631.5%
 
3.402e+173561.4%
 
Other values (424)1604164.5%
 
ValueCountFrequency (%) 
1.4108e+172< 0.1%
 
1.4108e+171< 0.1%
 
1.4108e+17610.2%
 
1.4108e+17690.3%
 
3.4e+173< 0.1%
 
ValueCountFrequency (%) 
4e+171< 0.1%
 
4e+17320.1%
 
4e+171< 0.1%
 
4e+17620.2%
 
4e+171100.4%
 

adbusign
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
0
24795 
1
 
70
ValueCountFrequency (%) 
02479599.7%
 
1700.3%
 
2020-12-01T17:20:29.020688image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

townsign
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
1
14383 
0
10482 
ValueCountFrequency (%) 
11438357.8%
 
01048242.2%
 
2020-12-01T17:20:29.311581image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

regtype
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
1
23792 
3
 
1025
4
 
48
ValueCountFrequency (%) 
12379295.7%
 
310254.1%
 
4480.2%
 
2020-12-01T17:20:29.579116image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T17:20:29.821520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:20:30.132499image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

empnum
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct62
Distinct (%)0.3%
Missing5250
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean4.397960744
Minimum0
Maximum1500
Zeros1100
Zeros (%)4.4%
Memory size194.3 KiB
2020-12-01T17:20:30.490662image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile10
Maximum1500
Range1500
Interquartile range (IQR)3

Descriptive statistics

Standard deviation15.38920562
Coefficient of variation (CV)3.499168481
Kurtosis5515.640328
Mean4.397960744
Median Absolute Deviation (MAD)1
Skewness64.09544801
Sum86266
Variance236.8276496
MonotocityNot monotonic
2020-12-01T17:20:30.812622image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3528421.3%
 
2467818.8%
 
123089.3%
 
520598.3%
 
412134.9%
 
011004.4%
 
108633.5%
 
66312.5%
 
83071.2%
 
202170.9%
 
Other values (52)9553.8%
 
(Missing)525021.1%
 
ValueCountFrequency (%) 
011004.4%
 
123089.3%
 
2467818.8%
 
3528421.3%
 
412134.9%
 
ValueCountFrequency (%) 
15001< 0.1%
 
10001< 0.1%
 
5001< 0.1%
 
3001< 0.1%
 
2181< 0.1%
 

compform
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing14234
Missing (%)57.2%
Memory size194.3 KiB
1
10610 
2
 
21
ValueCountFrequency (%) 
11061042.7%
 
2210.1%
 
(Missing)1423457.2%
 
2020-12-01T17:20:31.182410image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T17:20:31.463473image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:20:31.733051image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

parnum
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct51
Distinct (%)2.2%
Missing22526
Missing (%)90.6%
Infinite0
Infinite (%)0.0%
Mean4.587430526
Minimum0
Maximum100
Zeros3
Zeros (%)< 0.1%
Memory size194.3 KiB
2020-12-01T17:20:32.048398image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile23.1
Maximum100
Range100
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.752046576
Coefficient of variation (CV)1.907831961
Kurtosis18.62224191
Mean4.587430526
Median Absolute Deviation (MAD)0
Skewness4.094078848
Sum10730
Variance76.59831927
MonotocityNot monotonic
2020-12-01T17:20:32.379246image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
212304.9%
 
13991.6%
 
32931.2%
 
4960.4%
 
5490.2%
 
6300.1%
 
7210.1%
 
8130.1%
 
13130.1%
 
4411< 0.1%
 
Other values (41)1840.7%
 
(Missing)2252690.6%
 
ValueCountFrequency (%) 
03< 0.1%
 
13991.6%
 
212304.9%
 
32931.2%
 
4960.4%
 
ValueCountFrequency (%) 
1001< 0.1%
 
507< 0.1%
 
498< 0.1%
 
484< 0.1%
 
475< 0.1%
 

exenum
Real number (ℝ≥0)

MISSING
SKEWED

Distinct50
Distinct (%)3.6%
Missing23487
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean77.74963716
Minimum0
Maximum100000
Zeros10
Zeros (%)< 0.1%
Memory size194.3 KiB
2020-12-01T17:20:32.699768image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q33
95-th percentile36.15
Maximum100000
Range100000
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2693.742692
Coefficient of variation (CV)34.64636995
Kurtosis1377.958859
Mean77.74963716
Median Absolute Deviation (MAD)0
Skewness37.12059194
Sum107139
Variance7256249.693
MonotocityNot monotonic
2020-12-01T17:20:33.037094image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
18323.3%
 
21870.8%
 
3670.3%
 
5310.1%
 
4280.1%
 
6190.1%
 
1212< 0.1%
 
811< 0.1%
 
010< 0.1%
 
1010< 0.1%
 
Other values (40)1710.7%
 
(Missing)2348794.5%
 
ValueCountFrequency (%) 
010< 0.1%
 
18323.3%
 
21870.8%
 
3670.3%
 
4280.1%
 
ValueCountFrequency (%) 
1000001< 0.1%
 
501< 0.1%
 
496< 0.1%
 
488< 0.1%
 
474< 0.1%
 

opform
Categorical

MISSING

Distinct32
Distinct (%)0.4%
Missing15866
Missing (%)63.8%
Memory size194.3 KiB
10
8186 
01-以个人财产出资
 
575
01
 
159
服务
 
38
租赁
 
7
Other values (27)
 
34
ValueCountFrequency (%) 
10818632.9%
 
01-以个人财产出资5752.3%
 
011590.6%
 
服务380.2%
 
租赁7< 0.1%
 
咨询3< 0.1%
 
3< 0.1%
 
销售2< 0.1%
 
2< 0.1%
 
02-以家庭共有财产作为个人出资2< 0.1%
 
Other values (22)220.1%
 
(Missing)1586663.8%
 
2020-12-01T17:20:33.553954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique22 ?
Unique (%)0.2%
2020-12-01T17:20:33.890649image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length16
Median length3
Mean length2.825135733
Min length1

ptbusscope
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing24865
Missing (%)100.0%
Memory size194.4 KiB

venind
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing16428
Missing (%)66.1%
Memory size194.3 KiB
3
8115 
2
 
193
1
 
129
ValueCountFrequency (%) 
3811532.6%
 
21930.8%
 
11290.5%
 
(Missing)1642866.1%
 
2020-12-01T17:20:34.190897image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T17:20:34.476425image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:20:34.789989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

enttypeminu
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)0.4%
Missing17595
Missing (%)70.8%
Infinite0
Infinite (%)0.0%
Mean1824.567538
Minimum1121
Maximum4533
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:35.066742image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1121
5-th percentile1151
Q11151
median1151
Q31153
95-th percentile4533
Maximum4533
Range3412
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1339.867039
Coefficient of variation (CV)0.7343477351
Kurtosis0.3178476875
Mean1824.567538
Median Absolute Deviation (MAD)0
Skewness1.515983494
Sum13264606
Variance1795243.682
MonotocityNot monotonic
2020-12-01T17:20:35.364501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%) 
1151479519.3%
 
453313715.5%
 
11535682.3%
 
11523161.3%
 
4531500.2%
 
1222290.1%
 
1229290.1%
 
2151220.1%
 
1221210.1%
 
215310< 0.1%
 
Other values (16)590.2%
 
(Missing)1759570.8%
 
ValueCountFrequency (%) 
11211< 0.1%
 
11221< 0.1%
 
11238< 0.1%
 
1151479519.3%
 
11523161.3%
 
ValueCountFrequency (%) 
453313715.5%
 
45321< 0.1%
 
4531500.2%
 
22297< 0.1%
 
22231< 0.1%
 

midpreindcode
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing24865
Missing (%)100.0%
Memory size194.4 KiB

protype
Categorical

MISSING

Distinct2
Distinct (%)5.9%
Missing24831
Missing (%)99.9%
Memory size194.3 KiB
99
28 
1
ValueCountFrequency (%) 
99280.1%
 
16< 0.1%
 
(Missing)2483199.9%
 
2020-12-01T17:20:35.656810image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T17:20:35.901619image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:20:36.176066image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.001126081
Min length3

oploc
Categorical

HIGH CARDINALITY

Distinct5351
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size194.3 KiB
2367b4cac96d8598
18792 
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b19ffcd2880f506783bee75565895bdbb5
 
337
31487d8f256f16bd6244b7251be2ebb2ae36cd652943e86c8f0d6a96cbb90e3b
 
26
ca213febe80e171cf62c2ed671ebb5cbf19e3fe4b5809fbb
 
17
31487d8f256f16bd6244b7251be2ebb24d1db51663c654f53b92066f5b24275c
 
17
Other values (5346)
5676 
ValueCountFrequency (%) 
2367b4cac96d85981879275.6%
 
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b19ffcd2880f506783bee75565895bdbb53371.4%
 
31487d8f256f16bd6244b7251be2ebb2ae36cd652943e86c8f0d6a96cbb90e3b260.1%
 
ca213febe80e171cf62c2ed671ebb5cbf19e3fe4b5809fbb170.1%
 
31487d8f256f16bd6244b7251be2ebb24d1db51663c654f53b92066f5b24275c170.1%
 
31487d8f256f16bd6244b7251be2ebb24d1db51663c654f565ba1abf9b63dca00028eddeb16615db150.1%
 
31487d8f256f16bd6244b7251be2ebb27b17bdfd95c8f3b126d9320b9f534149140.1%
 
31487d8f256f16bd6244b7251be2ebb2b55c713be7e2b6d14f38dcde5525d37a130.1%
 
31487d8f256f16bd6244b7251be2ebb287440e1d026a5ecf8< 0.1%
 
ca213febe80e171c5ab458cd1d4bd374ad7fa6e4334fe50a7< 0.1%
 
Other values (5341)561922.6%
 
2020-12-01T17:20:36.504468image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5142 ?
Unique (%)20.7%
2020-12-01T17:20:36.806324image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length272
Median length16
Mean length39.96879147
Min length16

regcap
Real number (ℝ≥0)

SKEWED

Distinct1143
Distinct (%)4.6%
Missing191
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean5151.436626
Minimum0
Maximum5000100
Zeros6
Zeros (%)< 0.1%
Memory size194.3 KiB
2020-12-01T17:20:37.205327image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q115
median80
Q3500
95-th percentile5000
Maximum5000100
Range5000100
Interquartile range (IQR)485

Descriptive statistics

Standard deviation67770.85757
Coefficient of variation (CV)13.15571995
Kurtosis2024.844535
Mean5151.436626
Median Absolute Deviation (MAD)70
Skewness37.58223561
Sum127106547.3
Variance4592889136
MonotocityNot monotonic
2020-12-01T17:20:37.524186image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10521021.0%
 
100305412.3%
 
500277811.2%
 
50259310.4%
 
2016536.6%
 
100011174.5%
 
20010284.1%
 
3010164.1%
 
157172.9%
 
3004761.9%
 
Other values (1133)503220.2%
 
ValueCountFrequency (%) 
06< 0.1%
 
0.52< 0.1%
 
0.741< 0.1%
 
15< 0.1%
 
22< 0.1%
 
ValueCountFrequency (%) 
50001001< 0.1%
 
40040001< 0.1%
 
23501001< 0.1%
 
21985601< 0.1%
 
21292201< 0.1%
 

reccap
Real number (ℝ≥0)

MISSING
ZEROS

Distinct597
Distinct (%)8.4%
Missing17781
Missing (%)71.5%
Infinite0
Infinite (%)0.0%
Mean4198.165759
Minimum0
Maximum1278900
Zeros3641
Zeros (%)14.6%
Memory size194.3 KiB
2020-12-01T17:20:37.823396image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3100
95-th percentile10000
Maximum1278900
Range1278900
Interquartile range (IQR)100

Descriptive statistics

Standard deviation36537.97552
Coefficient of variation (CV)8.703318929
Kurtosis420.9530509
Mean4198.165759
Median Absolute Deviation (MAD)0
Skewness17.93697486
Sum29739806.24
Variance1335023655
MonotocityNot monotonic
2020-12-01T17:20:38.141401image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0364114.6%
 
505002.0%
 
1004241.7%
 
103411.4%
 
5001810.7%
 
10001700.7%
 
2001680.7%
 
301470.6%
 
201090.4%
 
300730.3%
 
Other values (587)13305.3%
 
(Missing)1778171.5%
 
ValueCountFrequency (%) 
0364114.6%
 
0.11< 0.1%
 
0.21< 0.1%
 
0.41< 0.1%
 
0.55< 0.1%
 
ValueCountFrequency (%) 
12789001< 0.1%
 
9801001< 0.1%
 
7174371< 0.1%
 
7154801< 0.1%
 
7122501< 0.1%
 

forreccap
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)4.8%
Missing24638
Missing (%)99.1%
Infinite0
Infinite (%)0.0%
Mean292.6444672
Minimum0
Maximum15428.17
Zeros217
Zeros (%)0.9%
Memory size194.3 KiB
2020-12-01T17:20:38.424594image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15428.17
Range15428.17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1841.310231
Coefficient of variation (CV)6.291970078
Kurtosis52.97308652
Mean292.6444672
Median Absolute Deviation (MAD)0
Skewness7.171911167
Sum66430.29406
Variance3390423.368
MonotocityNot monotonic
2020-12-01T17:20:38.754782image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
02170.9%
 
18.2265551< 0.1%
 
142501< 0.1%
 
50001< 0.1%
 
293.7851< 0.1%
 
2103.51< 0.1%
 
150001< 0.1%
 
80001< 0.1%
 
1436.61251< 0.1%
 
49001< 0.1%
 
(Missing)2463899.1%
 
ValueCountFrequency (%) 
02170.9%
 
18.2265551< 0.1%
 
293.7851< 0.1%
 
1436.61251< 0.1%
 
2103.51< 0.1%
 
ValueCountFrequency (%) 
15428.171< 0.1%
 
150001< 0.1%
 
142501< 0.1%
 
80001< 0.1%
 
50001< 0.1%
 

forregcap
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct38
Distinct (%)15.2%
Missing24615
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean1212.583484
Minimum0
Maximum88817.92045
Zeros210
Zeros (%)0.8%
Memory size194.3 KiB
2020-12-01T17:20:39.253137image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1109.8875
Maximum88817.92045
Range88817.92045
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8113.267914
Coefficient of variation (CV)6.690894294
Kurtosis80.3607255
Mean1212.583484
Median Absolute Deviation (MAD)0
Skewness8.678020629
Sum303145.871
Variance65825116.25
MonotocityNot monotonic
2020-12-01T17:20:39.614101image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%) 
02100.8%
 
902< 0.1%
 
3002< 0.1%
 
2002< 0.1%
 
999.751< 0.1%
 
6501< 0.1%
 
28.331< 0.1%
 
14901< 0.1%
 
681< 0.1%
 
651< 0.1%
 
Other values (28)280.1%
 
(Missing)2461599.0%
 
ValueCountFrequency (%) 
02100.8%
 
121< 0.1%
 
201< 0.1%
 
28.331< 0.1%
 
351< 0.1%
 
ValueCountFrequency (%) 
88817.920451< 0.1%
 
700001< 0.1%
 
500001< 0.1%
 
315001< 0.1%
 
142501< 0.1%
 

congro
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)13.3%
Missing24616
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean2805.259428
Minimum0
Maximum221453.7613
Zeros210
Zeros (%)0.8%
Memory size194.3 KiB
2020-12-01T17:20:39.927345image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4960
Maximum221453.7613
Range221453.7613
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18131.95415
Coefficient of variation (CV)6.463556977
Kurtosis100.7939374
Mean2805.259428
Median Absolute Deviation (MAD)0
Skewness9.519929349
Sum698509.5975
Variance328767761.2
MonotocityNot monotonic
2020-12-01T17:20:40.238964image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
02100.8%
 
1003< 0.1%
 
5003< 0.1%
 
30002< 0.1%
 
10002< 0.1%
 
150002< 0.1%
 
45001< 0.1%
 
14201< 0.1%
 
3001< 0.1%
 
23823.934841< 0.1%
 
Other values (23)230.1%
 
(Missing)2461699.0%
 
ValueCountFrequency (%) 
02100.8%
 
1003< 0.1%
 
1181< 0.1%
 
130.19131< 0.1%
 
1401< 0.1%
 
ValueCountFrequency (%) 
221453.76131< 0.1%
 
1400001< 0.1%
 
945001< 0.1%
 
500001< 0.1%
 
300001< 0.1%
 

enttypegb
Real number (ℝ≥0)

HIGH CORRELATION

Distinct53
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4256.337261
Minimum1110
Maximum9600
Zeros0
Zeros (%)0.0%
Memory size194.3 KiB
2020-12-01T17:20:40.587375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1110
5-th percentile1130
Q11130
median1152
Q39600
95-th percentile9600
Maximum9600
Range8490
Interquartile range (IQR)8470

Descriptive statistics

Standard deviation3873.165231
Coefficient of variation (CV)0.9099761118
Kurtosis-1.565109995
Mean4256.337261
Median Absolute Deviation (MAD)22
Skewness0.5700739104
Sum105833826
Variance15001408.91
MonotocityNot monotonic
2020-12-01T17:20:40.934783image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
9600819332.9%
 
1130746730.0%
 
1151479519.3%
 
453313715.5%
 
11908433.4%
 
45407573.0%
 
11535682.3%
 
11523161.3%
 
1110790.3%
 
2130770.3%
 
Other values (43)3991.6%
 
ValueCountFrequency (%) 
1110790.3%
 
11211< 0.1%
 
11221< 0.1%
 
11238< 0.1%
 
1130746730.0%
 
ValueCountFrequency (%) 
9600819332.9%
 
9100230.1%
 
68102< 0.1%
 
61801< 0.1%
 
61504< 0.1%
 

Interactions

2020-12-01T17:18:52.670575image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:52.947176image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:53.197078image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:53.473840image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:53.857372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:54.133570image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:54.383436image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:54.633268image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:54.897698image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:55.147600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:55.405756image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:55.670288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:55.925778image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:56.185640image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:56.575433image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:56.895262image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:57.179913image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:57.549715image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:18:58.603984image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:58.849343image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:59.107064image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:59.358521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:18:59.734378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:00.004200image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:00.295940image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:00.595780image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:01.355638image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:01.901658image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:02.657674image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:02.902128image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:03.157845image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:03.407677image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:06.898216image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:07.397944image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:10.485282image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:10.755104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:11.005003image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:11.284822image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:11.544683image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:11.782622image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:18.427934image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T17:19:18.677801image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-01T17:19:21.988388image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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Correlations

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Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
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Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
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Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
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Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

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Sample

First rows

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259b38c56de3836838082cfcb1a298951abfe15e6940c49ba340202R9053.031487d8f256f16bd6244b7251be2ebb2ae36cd652943e86c796096c38284d710f0f450a398f1b32cfaed0578b903293f40feb9e3800e9d3b文化娱乐经纪人服务;境内文艺活动组织与策划;文化艺术交流活动组织策划;演出经纪;其他文化艺术经纪代理;文化娱乐经纪人;网络营销策划;市场营销策划;企业形象策划咨询;网上从事企业形象策划服务;企业营销策划;品牌策划服务;广告设计、制作、发布、代理;影视、广播广告发布服务;广告代理服务;互联网广告服务(依法须经批准的项目,经相关部门批准后方可开展经营活动)。11001150.02020-09-14 14:46:30NaN63402020100100000004000000000007539100012.0NaN1.0NaNNaNNaNNaN1151.0NaNNaN2367b4cac96d8598100.0NaNNaNNaNNaN1151
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4f000950527a6feb63ee1ce82bb22ddd1ab8b8fdffa3b91fb340202R8810.031487d8f256f16bd6244b7251be2ebb2ae36cd652943e86cfd2e8fa08b3f80b6e3173f8c796457bf2ebc14ea2d3c1be5cefbd12b724f133dcb205d324d0c6c7fc49cb7baf29b4dfe境内文化艺术交流活动策划;企业形象策划;礼仪庆典服务;翻译服务;专利代理;广告设计、制作、代理、发布。11001130.02017-12-012067-11-307340200000000000000400000000000283237001NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN2367b4cac96d8598100.0NaNNaNNaNNaN1130
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